A01=Kristian Skrede Gleditsch
A01=Michael D. Ward
Age Group_Uncategorized
Age Group_Uncategorized
Author_Kristian Skrede Gleditsch
Author_Michael D. Ward
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Category1=Non-Fiction
Category=JHBC
continuous dependent variables
COP=United States
Delivery_Delivery within 10-20 working days
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eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Exploratory Spatial analysis
Language_English
mapping data
PA=Available
Price_€20 to €50
PS=Active
QASS
Quantitative Applications in the Social Sciences
regressors
softlaunch
Spatial Regression Models
Product details
- ISBN 9781544328836
- Weight: 160g
- Dimensions: 139 x 215mm
- Publication Date: 26 Jul 2018
- Publisher: SAGE Publications Inc
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The text covers different modeling-related topics for continuous dependent variables, including mapping data on spatial units, creating data from maps, analyzing exploratory spatial data, working with regression models that have spatially dependent regressors, and estimating regression models with spatially correlated error structures.
Using social science examples based on real data, the authors illustrate the concepts discussed, and show how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the R package for statistical computing. Users can download both the data and computer code to work through all the examples found in the text. New to the Second Edition is a chapter on mapping as data exploration and its role in the research process, updates to all chapters based on substantive and methodological work, as well as software updates, and information on estimation of time-series, cross-sectional spatial models.
Using social science examples based on real data, the authors illustrate the concepts discussed, and show how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the R package for statistical computing. Users can download both the data and computer code to work through all the examples found in the text. New to the Second Edition is a chapter on mapping as data exploration and its role in the research process, updates to all chapters based on substantive and methodological work, as well as software updates, and information on estimation of time-series, cross-sectional spatial models.
Michael D. Ward is Professor of Political Science at Duke University. He is an affiliate of the Duke Network Analysis Center. His primary interests are in international relations (spanning democratization, globalization, international commerce, military spending, as well as international conflict and cooperation), political geography, as well as mathematical and statistical methods. Kristian Skrede Gleditsch is Professor in the Department of Government, University of Essex and a Research Associate at the Centre for the Study of Civil War, PRIO. His research interests include conflict and cooperation, democratization, and spatial dimensions of social and political processes. He is the author of All International Politics is Local: The Diffusion of Conflict, Integration, and Democratization (University of Michigan Press, 2002) and Spatial Regression Models (Sage, 2008, with Michael D. Ward) as well as articles in journals including American Journal of Political Science, American Political Science Review, Annals of the Association of American Geographers, Biological Reviews, International Interactions, International Organization, International Studies Quarterly, Journal of Conflict Resolution, Journal of Peace Research, Political Analysis, Political Psychology, and World Politics.
